| A deep learning framework for financial time series using stacked autoencoders and long-short term memory W Bao, J Yue, Y Rao PloS one 12 (7), e0180944, 2017 | 1116 | 2017 |
| Spectral–spatial classification of hyperspectral images using deep convolutional neural networks J Yue, W Zhao, S Mao, H Liu Remote Sensing Letters 6 (6), 468-477, 2015 | 526 | 2015 |
| On combining multiscale deep learning features for the classification of hyperspectral remote sensing imagery W Zhao, Z Guo, J Yue, X Zhang, L Luo International Journal of Remote Sensing 36 (13), 3368-3379, 2015 | 205 | 2015 |
| A deep learning framework for hyperspectral image classification using spatial pyramid pooling J Yue, S Mao, M Li Remote Sensing Letters 7 (9), 875-884, 2016 | 138 | 2016 |
| Self-supervised learning with adaptive distillation for hyperspectral image classification J Yue, L Fang, H Rahmani, P Ghamisi IEEE Transactions on Geoscience and Remote Sensing 60, 1-13, 2021 | 97 | 2021 |
| Global prototypical network for few-shot hyperspectral image classification C Zhang, J Yue, Q Qin IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2020 | 55 | 2020 |
| Deep bilateral filtering network for point-supervised semantic segmentation in remote sensing images L Wu, L Fang, J Yue, B Zhang, P Ghamisi, M He IEEE Transactions on Image Processing 31, 7419-7434, 2022 | 36 | 2022 |
| Spectral-spatial latent reconstruction for open-set hyperspectral image classification J Yue, L Fang, M He IEEE Transactions on Image Processing 31, 5227-5241, 2022 | 36 | 2022 |
| Hyperspectral image instance segmentation using spectral–spatial feature pyramid network L Fang, Y Jiang, Y Yan, J Yue, Y Deng IEEE Transactions on Geoscience and Remote Sensing 61, 1-13, 2023 | 33 | 2023 |
| Optical remote sensing image understanding with weak supervision: Concepts, methods, and perspectives J Yue, L Fang, P Ghamisi, W Xie, J Li, J Chanussot, A Plaza IEEE Geoscience and Remote Sensing Magazine 10 (2), 250-269, 2022 | 31 | 2022 |
| Discrepant multiple instance learning for weakly supervised object detection W Gao, F Wan, J Yue, S Xu, Q Ye Pattern Recognition 122, 108233, 2022 | 30 | 2022 |
| Large-scale few-shot learning via multi-modal knowledge discovery S Wang, J Yue, J Liu, Q Tian, M Wang Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 27 | 2020 |
| Dif-fusion: Towards high color fidelity in infrared and visible image fusion with diffusion models J Yue, L Fang, S Xia, Y Deng, J Ma IEEE Transactions on Image Processing, 2023 | 25 | 2023 |
| Adaptive spatial pyramid constraint for hyperspectral image classification with limited training samples J Yue, D Zhu, L Fang, P Ghamisi, Y Wang IEEE Transactions on Geoscience and Remote Sensing 60, 1-14, 2021 | 25 | 2021 |
| A time varying ventilation and dust control strategy based on the temporospatial characteristics of dust dispersion H Liu, X Wu, S Mao, M Li, J Yue Minerals 7 (4), 59, 2017 | 24 | 2017 |
| Application of luojia 1-01 nighttime images for detecting the light changes for the 2019 spring festival in western cities, China C Zhang, Y Pei, J Li, Q Qin, J Yue Remote Sensing 12 (9), 1416, 2020 | 21 | 2020 |
| Deep quadruplet network for hyperspectral image classification with a small number of samples C Zhang, J Yue, Q Qin Remote Sensing 12 (4), 647, 2020 | 20 | 2020 |
| 基于 CMVS/PMVS 多视角密集匹配方法的研究与实现 何豫航， 岳俊 测绘地理信息 38 (3), 20-23, 2013 | 19 | 2013 |
| SpectralDiff: A generative framework for hyperspectral image classification with diffusion models N Chen, J Yue, L Fang, S Xia IEEE Transactions on Geoscience and Remote Sensing, 2023 | 17* | 2023 |
| Geometric-spectral reconstruction learning for multi-source open-set classification with hyperspectral and LiDAR data L Fang, D Zhu, J Yue, B Zhang, M He IEEE/CAA Journal of Automatica Sinica 9 (10), 1892-1895, 2022 | 16 | 2022 |
Leyuan FangProfessor in College of Electrical and Information Engineering, Hunan UniversityVerified email at hnu.edu.cn
